The keyboard event models are inconsistent across different Smartphone and mobile platforms and identifying a dwell time for a key click on a touch screen seems unfeasible at this time because the programmatic UITouch class in Apple iOS, for example, cannot be utilized due to the fact that a keyboard automatically pops up and disables touch events when user tries to type in the iOS. The keystroke capture measurement of a user's typing flight time alone is not distinguishable to succinctly identify an individual, and would therefore offer very limited value in the authentication scheme. Many keystroke algorithms are built around the consistency of dwell values, which is how long a user presses a key, for a particular user. Therefore, the QWERTY keyboard biometrics, especially dwell time, are unsuited to touch screen displays and a color pattern usage is more intuitive for a natural user interaction.
Keystroke algorithms do not utilize features of touch screen devices that could provide further insight in to the identity of the owner. While known systems employ the idea of using graphical and/or touch (gesture) passwords for authentication, they are not known to use the attributes of the particular touch events. Such systems use continuous gestures as passwords, comparing the drawn gesture to previously trained gestures. They do not use discrete touch events, each with a range of characterizing elements.
There are additionally previous patents using discrete touches, but use the touches to perfectly recreate a previous set of selections. For example, selecting a series of points on a displayed photograph or selecting the correct subset from a grid of icons. The user is granted access if the match is perfect. There is no intelligent confidence factor based on how similar the current login touches are to previous touches.
What is needed, therefore, are techniques for biometrically authenticating a user based on attributes of a sequence of touch events.